Comparison
DeepResearch vs storm
DeepResearch (Tongyi Deep Research, the Leading Open-source Deep Research Agent) vs storm (An LLM-powered knowledge curation system that researches a topic and generates full-length reports with citations.) - live GitHub stats and typed graph relationships, not marketing.
Markdown twin · DeepResearch alternatives · storm alternatives
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Tagline
- DeepResearch
- Tongyi Deep Research, the Leading Open-source Deep Research Agent
- storm
- An LLM-powered knowledge curation system that researches a topic and generates full-length reports with citations.
Stars
- DeepResearch
- 20k
- storm
- 30k
Forks
- DeepResearch
- 1.5k
- storm
- 2.8k
Open issues
- DeepResearch
- 91
- storm
- 123
Language
- DeepResearch
- Python
- storm
- Python
Adopt for
- DeepResearch
- DeepResearch is an agentic large language model designed with a focus on long-horizon, deep information-seeking tasks, making it particularly suitable for users needing advanced search capabilities. It comes with 30.5B+3
- storm
- STORM is an LLM-powered knowledge curation system that uses agentic-RAG for deep research to generate full-length reports with citations.
Persona
- DeepResearch
- -
- storm
- -
Runtime
- DeepResearch
- -
- storm
- -
License
- DeepResearch
- Apache-2.0
- storm
- MIT
Last pushed
- DeepResearch
- Feb 27, 2026
- storm
- Sep 30, 2025
Categories
- DeepResearch
- AI Agents, LLM Frameworks
- storm
- Data & Retrieval, LLM Frameworks
Trust and health
Days since push
- DeepResearch
- 130d
- storm
- 281d
Open issues (now)
- DeepResearch
- 91
- storm
- 123
Security scan
- DeepResearch
- 104 low (104 low)
- storm
- No criticals
Full report
- DeepResearch
- Trust report
- storm
- Trust report
Typed relationship
DeepResearch alternative stormBoth platforms are built for deep research using LLMs, with similar goals in mind but likely differing in implementation and features.
Choose DeepResearch if…
- License: DeepResearch is Apache-2.0, storm is MIT.
- Pricing: No specific pricing info provided; deployment could vary depending on your cloud service provider or if you self-host on local servers..
- Requirements: Min 16 GB RAM; Requires substantial computational resources due to its size and complexity.; Recommended for users with access to robust hardware infrastructure, either through cloud services like Aliyun's Bailian or local deployment..
- Both platforms are built for deep research using LLMs, with similar goals in mind but likely differing in implementation and features.
- Tags unique to DeepResearch: llm, artificial-intelligence, alibaba, web-agent.
- Also covers AI Agents.
- When you need to perform sophisticated long-term horizon tasks that require in-depth information seeking.
When NOT to use DeepResearch
- Avoid using it for tasks requiring quick responses as it might suffer from slower response times due to its complex architecture designed for deep information-seeking.
- Not suitable for less demanding or simpler tasks where smaller and more efficient models can perform adequately without the overhead of DeepResearch's extensive capability.
Choose storm if…
- License: storm is MIT, DeepResearch is Apache-2.0.
- Both platforms are built for deep research using LLMs, with similar goals in mind but likely differing in implementation and features.
- Tags unique to storm: large-language-models, report-generation, retrieval-augmented-generation, knowledge-curation.
- Also covers Data & Retrieval.
- When you need a tool capable of generating comprehensive and cited reports based on deep research.
When NOT to use storm
- Avoid STORM if cost optimization is critical as it may involve using multiple different models to balance between quality and expense.
- Do not choose STORM if you require a tool that does not modify its behavior through agentic-RAG processes, which are central to this system’s operation.
Explore
DeepResearch trust report →storm trust report →AI Agents category →LLM Frameworks category →Data & Retrieval category →All comparisonsStack workflowsTrending tools
Related comparisons
Common questions
- What is the difference between DeepResearch and storm?
- DeepResearch: Tongyi Deep Research, the Leading Open-source Deep Research Agent. storm: An LLM-powered knowledge curation system that researches a topic and generates full-length reports with citations.. See the comparison table for live GitHub stats and shared categories.
- When should I choose DeepResearch over storm?
- Choose DeepResearch over storm when License: DeepResearch is Apache-2.0, storm is MIT; Pricing: No specific pricing info provided; deployment could vary depending on your cloud service provider or if you self-host on local servers.; Requirements: Min 16 GB RAM; Requires substantial computational resources due to its size and complexity.; Recommended for users with access to robust hardware infrastructure, either through cloud services like Aliyun's Bailian or local deployment.; Both platforms are built for deep research using LLMs, with similar goals in mind but likely differing in implementation and features; Tags unique to DeepResearch: llm, artificial-intelligence, alibaba, web-agent; Also covers AI Agents; When you need to perform sophisticated long-term horizon tasks that require in-depth information seeking.
- When should I choose storm over DeepResearch?
- Choose storm over DeepResearch when License: storm is MIT, DeepResearch is Apache-2.0; Both platforms are built for deep research using LLMs, with similar goals in mind but likely differing in implementation and features; Tags unique to storm: large-language-models, report-generation, retrieval-augmented-generation, knowledge-curation; Also covers Data & Retrieval; When you need a tool capable of generating comprehensive and cited reports based on deep research.
- When should I avoid DeepResearch?
- Avoid using it for tasks requiring quick responses as it might suffer from slower response times due to its complex architecture designed for deep information-seeking. Not suitable for less demanding or simpler tasks where smaller and more efficient models can perform adequately without the overhead of DeepResearch's extensive capability.
- When should I avoid storm?
- Avoid STORM if cost optimization is critical as it may involve using multiple different models to balance between quality and expense. Do not choose STORM if you require a tool that does not modify its behavior through agentic-RAG processes, which are central to this system’s operation.
- Is DeepResearch or storm more popular on GitHub?
- storm has more GitHub stars (29,951 vs 19,621). Stars measure visibility, not whether either tool fits your constraints.
- Are DeepResearch and storm open source?
- Yes - both are open-source projects on GitHub (DeepResearch: Apache-2.0, storm: MIT).
- Where can I find alternatives to DeepResearch or storm?
- GraphCanon lists graph-backed alternatives at /tools/alibaba-nlp-deepresearch/alternatives and /tools/stanford-oval-storm/alternatives (/tools/alibaba-nlp-deepresearch/alternatives.md, /tools/stanford-oval-storm/alternatives.md), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at /compare/alibaba-nlp-deepresearch-vs-stanford-oval-storm.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, DeepResearch or storm?
- DeepResearch: Slowing. storm: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for DeepResearch and storm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepResearch: /tools/alibaba-nlp-deepresearch/trust; storm: /tools/stanford-oval-storm/trust.